imgglobalpca.m

matlab获取PCA特征的小程序

% this function is used to obtain pca feature for a training set or a test set

function s=imgglobalpca(tsign)

pnum = 3648;
bname = 'img_';

inum = 2;
cnum = 1199;
dim  = 456;

ipath = strcat('E:\FYC_FERET\pimages\',bname,tsign,'\');
dpath = 'E:\FYC_FERET\datas\';
rname = strcat(dpath,'fea\glo_',tsign,'.dat');

%load parameters
ename     = strcat(dpath,'para\','pcaef_',tsign,'.dat');
eigenface = load(ename);
eigenface = eigenface(:,1:dim);
aname     = strcat(dpath,'para\','pcaaf_',tsign,'.dat');
averface  = load(aname);
averface  = averface';
%init result matrix
feamat = zeros(dim,cnum*inum);
%create the file path and name and read out source data
for i=1:cnum
    filepath = int2str(i);
    imgpath  = strcat(ipath,filepath,'\');
    for j=1:inum
        [i j]
        filename=int2str(j);
        imnam = strcat(imgpath,filename,'.bmp')   
        image = imread(imnam,'bmp');
        image = double(image)/255;
        [imhei,imwid,cdim] = size(image);
        immat = zeros(pnum,1);
        count = 0;
        for ii=1:imhei
            for jj=1:imwid
                if ~( image(ii,jj,1)==0 & image(ii,jj,2)==0 & image(ii,jj,3)==1 )
                    count = count+1;
                    immat(count) = image(ii,jj,1);
                end
            end
        end
        if count~=pnum
            fprintf(1,'mask error...');
            [ count pnum ]
            pause;
        end
        feamat(:,(i-1)*inum+j) = pcafea(immat,averface,eigenface);      
    end
end 
fprintf(1,'Finishing calculate the feature...');
%pause

max(max(feamat))
pause

fid=fopen(rname,'w+t');
for i=1:dim
    i
    for j=1:cnum*inum
        fprintf(fid,'%12.6f ',feamat(i,j));
    end
    fprintf(fid,'\n');
end
fclose(fid);
fprintf(1,'Finishing store the feature...');

s=1;